My research interests have been in the data analytics area for over twenty years. I am interested in new computational techniques for analytics as well as innovative applications of analytics in business. On the algorithmic side my interests have primarily been on pattern discovery algorithms. The focus of these methods is typically the discovery of new and actionable insights from data.

On the application domains my interests have been in applying analytics techniques in application areas such as news recommender systems, healthcare, customer churn analytics, behavioral profiling and predicting presidential elections. Here my focus tends to be innovation in the application domain and typically my research tries to take a novel perspective to an existing problem. In churn analytics for instance we bring in a psychology and behavioral economics perspective. In news recommender systems the aim is to uncover unexpected pitfalls of common algorithms and design new solutions to address these. In predicting election outcomes our research focuses on extracting signals from television viewership data as a proxy for predicting which candidates might win. In healthcare we study how analytics to reduce costs can benefit from experiments and network diffusion ideas. In behavioral profiling my research looks at learning user patterns as well as active learning to help customer analytics.

My research tends to have both direct and indirect implications to information systems design and use. Increasingly information systems tend to support high impact analytics initiatives and understanding the relationship between systems, analytics, people and applications is crucial for business success.